Upload PPO LunarLander-v2 trained agent

README.md

@@ -0,0 +1,37 @@
+---
+library_name: stable-baselines3
+tags:
+- LunarLander-v2
+- deep-reinforcement-learning
+- reinforcement-learning
+- stable-baselines3
+model-index:
+- name: PPO
+  results:
+  - task:
+      type: reinforcement-learning
+      name: reinforcement-learning
+    dataset:
+      name: LunarLander-v2
+      type: LunarLander-v2
+    metrics:
+    - type: mean_reward
+      value: 242.34 +/- 12.29
+      name: mean_reward
+      verified: false
+---
+
+# **PPO** Agent playing **LunarLander-v2**
+This is a trained model of a **PPO** agent playing **LunarLander-v2**
+using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3).
+
+## Usage (with Stable-baselines3)
+TODO: Add your code
+
+
+```python
+from stable_baselines3 import ...
+from huggingface_sb3 import load_from_hub
+
+...
+```

config.json

@@ -0,0 +1 @@
+{"policy_class": {":type:": "<class 'abc.ABCMeta'>", ":serialized:": "gAWVOwAAAAAAAACMIXN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbi5wb2xpY2llc5SMEUFjdG9yQ3JpdGljUG9saWN5lJOULg==", "__module__": "stable_baselines3.common.policies", "__doc__": "\n    Policy class for actor-critic algorithms (has both policy and value prediction).\n    Used by A2C, PPO and the likes.\n\n    :param observation_space: Observation space\n    :param action_space: Action space\n    :param lr_schedule: Learning rate schedule (could be constant)\n    :param net_arch: The specification of the policy and value networks.\n    :param activation_fn: Activation function\n    :param ortho_init: Whether to use or not orthogonal initialization\n    :param use_sde: Whether to use State Dependent Exploration or not\n    :param log_std_init: Initial value for the log standard deviation\n    :param full_std: Whether to use (n_features x n_actions) parameters\n        for the std instead of only (n_features,) when using gSDE\n    :param sde_net_arch: Network architecture for extracting features\n        when using gSDE. If None, the latent features from the policy will be used.\n        Pass an empty list to use the states as features.\n    :param use_expln: Use ``expln()`` function instead of ``exp()`` to ensure\n        a positive standard deviation (cf paper). It allows to keep variance\n        above zero and prevent it from growing too fast. In practice, ``exp()`` is usually enough.\n    :param squash_output: Whether to squash the output using a tanh function,\n        this allows to ensure boundaries when using gSDE.\n    :param features_extractor_class: Features extractor to use.\n    :param features_extractor_kwargs: Keyword arguments\n        to pass to the features extractor.\n    :param normalize_images: Whether to normalize images or not,\n         dividing by 255.0 (True by default)\n    :param optimizer_class: The optimizer to use,\n        ``th.optim.Adam`` by default\n    :param optimizer_kwargs: Additional keyword arguments,\n        excluding the learning rate, to pass to the optimizer\n    ", "__init__": "<function ActorCriticPolicy.__init__ at 0x7f987e64baf0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f987e64bb80>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f987e64bc10>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f987e64bca0>", "_build": "<function ActorCriticPolicy._build at 0x7f987e64bd30>", "forward": "<function ActorCriticPolicy.forward at 0x7f987e64bdc0>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f987e64be50>", "_predict": "<function ActorCriticPolicy._predict at 0x7f987e64bee0>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f987e64bf70>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f987e651040>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f987e6510d0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7f987e64d180>"}, "verbose": 1, "policy_kwargs": {}, "observation_space": {":type:": "<class 'gym.spaces.box.Box'>", ":serialized:": "gAWVnwEAAAAAAACMDmd5bS5zcGFjZXMuYm94lIwDQm94lJOUKYGUfZQojAVkdHlwZZSMBW51bXB5lGgFk5SMAmY0lImIh5RSlChLA4wBPJROTk5K/////0r/////SwB0lGKMBl9zaGFwZZRLCIWUjANsb3eUjBJudW1weS5jb3JlLm51bWVyaWOUjAtfZnJvbWJ1ZmZlcpSTlCiWIAAAAAAAAAAAAID/AACA/wAAgP8AAID/AACA/wAAgP8AAID/AACA/5RoCksIhZSMAUOUdJRSlIwEaGlnaJRoEiiWIAAAAAAAAAAAAIB/AACAfwAAgH8AAIB/AACAfwAAgH8AAIB/AACAf5RoCksIhZRoFXSUUpSMDWJvdW5kZWRfYmVsb3eUaBIolggAAAAAAAAAAAAAAAAAAACUaAeMAmIxlImIh5RSlChLA4wBfJROTk5K/////0r/////SwB0lGJLCIWUaBV0lFKUjA1ib3VuZGVkX2Fib3ZllGgSKJYIAAAAAAAAAAAAAAAAAAAAlGghSwiFlGgVdJRSlIwKX25wX3JhbmRvbZROdWIu", "dtype": "float32", "_shape": [8], "low": "[-inf -inf -inf -inf -inf -inf -inf -inf]", "high": "[inf inf inf inf inf inf inf inf]", "bounded_below": "[False False False False False False False False]", "bounded_above": "[False False False False False False False False]", "_np_random": null}, "action_space": {":type:": "<class 'gym.spaces.discrete.Discrete'>", ":serialized:": "gAWVggAAAAAAAACME2d5bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpRLBIwGX3NoYXBllCmMBWR0eXBllIwFbnVtcHmUaAeTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYowKX25wX3JhbmRvbZROdWIu", "n": 4, "_shape": [], "dtype": "int64", "_np_random": null}, "n_envs": 16, "num_timesteps": 1015808, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1671133164858083139, "learning_rate": 0.0003, "tensorboard_log": null, "lr_schedule": {":type:": "<class 'function'>", ":serialized:": "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"}, "_last_obs": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "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"}, "_last_episode_starts": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVgwAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYQAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSxCFlIwBQ5R0lFKULg=="}, "_last_original_obs": null, "_episode_num": 0, "use_sde": false, "sde_sample_freq": -1, "_current_progress_remaining": -0.015808000000000044, "ep_info_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "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"}, "ep_success_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="}, "_n_updates": 248, "n_steps": 1024, "gamma": 0.999, "gae_lambda": 0.98, "ent_coef": 0.01, "vf_coef": 0.5, "max_grad_norm": 0.5, "batch_size": 64, "n_epochs": 4, "clip_range": {":type:": "<class 'function'>", ":serialized:": "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"}, "clip_range_vf": null, "normalize_advantage": true, "target_kl": null, "system_info": {"OS": "Linux-5.10.133+-x86_64-with-glibc2.27 #1 SMP Fri Aug 26 08:44:51 UTC 2022", "Python": "3.8.16", "Stable-Baselines3": "1.6.2", "PyTorch": "1.13.0+cu116", "GPU Enabled": "True", "Numpy": "1.21.6", "Gym": "0.21.0"}}

ppo-LunarLander-v2.zip

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:5902e54f4ade2938c0593b081ae080e1b491464c3ee0006ca4e25f7fa4ba14a7
+size 147214

ppo-LunarLander-v2/_stable_baselines3_version

@@ -0,0 +1 @@
+1.6.2

ppo-LunarLander-v2/data

@@ -0,0 +1,94 @@
+{
+    "policy_class": {
+        ":type:": "<class 'abc.ABCMeta'>",
+        ":serialized:": "gAWVOwAAAAAAAACMIXN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbi5wb2xpY2llc5SMEUFjdG9yQ3JpdGljUG9saWN5lJOULg==",
+        "__module__": "stable_baselines3.common.policies",
+        "__doc__": "\n    Policy class for actor-critic algorithms (has both policy and value prediction).\n    Used by A2C, PPO and the likes.\n\n    :param observation_space: Observation space\n    :param action_space: Action space\n    :param lr_schedule: Learning rate schedule (could be constant)\n    :param net_arch: The specification of the policy and value networks.\n    :param activation_fn: Activation function\n    :param ortho_init: Whether to use or not orthogonal initialization\n    :param use_sde: Whether to use State Dependent Exploration or not\n    :param log_std_init: Initial value for the log standard deviation\n    :param full_std: Whether to use (n_features x n_actions) parameters\n        for the std instead of only (n_features,) when using gSDE\n    :param sde_net_arch: Network architecture for extracting features\n        when using gSDE. If None, the latent features from the policy will be used.\n        Pass an empty list to use the states as features.\n    :param use_expln: Use ``expln()`` function instead of ``exp()`` to ensure\n        a positive standard deviation (cf paper). It allows to keep variance\n        above zero and prevent it from growing too fast. In practice, ``exp()`` is usually enough.\n    :param squash_output: Whether to squash the output using a tanh function,\n        this allows to ensure boundaries when using gSDE.\n    :param features_extractor_class: Features extractor to use.\n    :param features_extractor_kwargs: Keyword arguments\n        to pass to the features extractor.\n    :param normalize_images: Whether to normalize images or not,\n         dividing by 255.0 (True by default)\n    :param optimizer_class: The optimizer to use,\n        ``th.optim.Adam`` by default\n    :param optimizer_kwargs: Additional keyword arguments,\n        excluding the learning rate, to pass to the optimizer\n    ",
+        "__init__": "<function ActorCriticPolicy.__init__ at 0x7f987e64baf0>",
+        "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f987e64bb80>",
+        "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f987e64bc10>",
+        "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f987e64bca0>",
+        "_build": "<function ActorCriticPolicy._build at 0x7f987e64bd30>",
+        "forward": "<function ActorCriticPolicy.forward at 0x7f987e64bdc0>",
+        "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f987e64be50>",
+        "_predict": "<function ActorCriticPolicy._predict at 0x7f987e64bee0>",
+        "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f987e64bf70>",
+        "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f987e651040>",
+        "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f987e6510d0>",
+        "__abstractmethods__": "frozenset()",
+        "_abc_impl": "<_abc_data object at 0x7f987e64d180>"
+    },
+    "verbose": 1,
+    "policy_kwargs": {},
+    "observation_space": {
+        ":type:": "<class 'gym.spaces.box.Box'>",
+        ":serialized:": "gAWVnwEAAAAAAACMDmd5bS5zcGFjZXMuYm94lIwDQm94lJOUKYGUfZQojAVkdHlwZZSMBW51bXB5lGgFk5SMAmY0lImIh5RSlChLA4wBPJROTk5K/////0r/////SwB0lGKMBl9zaGFwZZRLCIWUjANsb3eUjBJudW1weS5jb3JlLm51bWVyaWOUjAtfZnJvbWJ1ZmZlcpSTlCiWIAAAAAAAAAAAAID/AACA/wAAgP8AAID/AACA/wAAgP8AAID/AACA/5RoCksIhZSMAUOUdJRSlIwEaGlnaJRoEiiWIAAAAAAAAAAAAIB/AACAfwAAgH8AAIB/AACAfwAAgH8AAIB/AACAf5RoCksIhZRoFXSUUpSMDWJvdW5kZWRfYmVsb3eUaBIolggAAAAAAAAAAAAAAAAAAACUaAeMAmIxlImIh5RSlChLA4wBfJROTk5K/////0r/////SwB0lGJLCIWUaBV0lFKUjA1ib3VuZGVkX2Fib3ZllGgSKJYIAAAAAAAAAAAAAAAAAAAAlGghSwiFlGgVdJRSlIwKX25wX3JhbmRvbZROdWIu",
+        "dtype": "float32",
+        "_shape": [
+            8
+        ],
+        "low": "[-inf -inf -inf -inf -inf -inf -inf -inf]",
+        "high": "[inf inf inf inf inf inf inf inf]",
+        "bounded_below": "[False False False False False False False False]",
+        "bounded_above": "[False False False False False False False False]",
+        "_np_random": null
+    },
+    "action_space": {
+        ":type:": "<class 'gym.spaces.discrete.Discrete'>",
+        ":serialized:": "gAWVggAAAAAAAACME2d5bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpRLBIwGX3NoYXBllCmMBWR0eXBllIwFbnVtcHmUaAeTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYowKX25wX3JhbmRvbZROdWIu",
+        "n": 4,
+        "_shape": [],
+        "dtype": "int64",
+        "_np_random": null
+    },
+    "n_envs": 16,
+    "num_timesteps": 1015808,
+    "_total_timesteps": 1000000,
+    "_num_timesteps_at_start": 0,
+    "seed": null,
+    "action_noise": null,
+    "start_time": 1671133164858083139,
+    "learning_rate": 0.0003,
+    "tensorboard_log": null,
+    "lr_schedule": {
+        ":type:": "<class 'function'>",
+        ":serialized:": "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"
+    },
+    "_last_obs": {
+        ":type:": "<class 'numpy.ndarray'>",
+        ":serialized:": "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"
+    },
+    "_last_episode_starts": {
+        ":type:": "<class 'numpy.ndarray'>",
+        ":serialized:": "gAWVgwAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYQAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSxCFlIwBQ5R0lFKULg=="
+    },
+    "_last_original_obs": null,
+    "_episode_num": 0,
+    "use_sde": false,
+    "sde_sample_freq": -1,
+    "_current_progress_remaining": -0.015808000000000044,
+    "ep_info_buffer": {
+        ":type:": "<class 'collections.deque'>",
+        ":serialized:": "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"
+    },
+    "ep_success_buffer": {
+        ":type:": "<class 'collections.deque'>",
+        ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="
+    },
+    "_n_updates": 248,
+    "n_steps": 1024,
+    "gamma": 0.999,
+    "gae_lambda": 0.98,
+    "ent_coef": 0.01,
+    "vf_coef": 0.5,
+    "max_grad_norm": 0.5,
+    "batch_size": 64,
+    "n_epochs": 4,
+    "clip_range": {
+        ":type:": "<class 'function'>",
+        ":serialized:": "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"
+    },
+    "clip_range_vf": null,
+    "normalize_advantage": true,
+    "target_kl": null
+}

ppo-LunarLander-v2/policy.optimizer.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:93f200917e6d08ceb8f1bea7f4043b61f3275ec66e02f5c2b12cb19f3aa3e2dd
+size 87929

ppo-LunarLander-v2/policy.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:b25155fbdea82d493791ec8d789165bee783e0ce15f0e3fb57f1b36f300e17c7
+size 43201

ppo-LunarLander-v2/pytorch_variables.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:d030ad8db708280fcae77d87e973102039acd23a11bdecc3db8eb6c0ac940ee1
+size 431

ppo-LunarLander-v2/system_info.txt

@@ -0,0 +1,7 @@
+OS: Linux-5.10.133+-x86_64-with-glibc2.27 #1 SMP Fri Aug 26 08:44:51 UTC 2022
+Python: 3.8.16
+Stable-Baselines3: 1.6.2
+PyTorch: 1.13.0+cu116
+GPU Enabled: True
+Numpy: 1.21.6
+Gym: 0.21.0

results.json

@@ -0,0 +1 @@
+{"mean_reward": 242.3363498651156, "std_reward": 12.291104592355017, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2022-12-15T20:03:36.977516"}